CODEWITHSUNDEEP
pythondependenciespython-packaging
FordPrefect
FordPrefect

Reputation: 406

Dependencies packages and subpackages

I am really new to python packaging. It already is a confusing topic with recommended ways and options that only a minority seems to apply. But to make it worse, I stumbled over this problem.

I started with the intention to write a rather small package with a really focussed purpose. My first solution included import of pandas. But I got the request to remove that dependency. So I tried to refactor the function and unsurprisingly it's slower. And slower to an extent that I can't hardly accept it.

So a solution would be to provide a package that uses pandas and a package that don't uses pandas. So that people can use either or, depending on project requirements. Now I am wondering what the best way is to provide that.

I could:

  1. Create two seperate projects with different package names. That would work, but I want to keep the code together and there are functions and code shared.
  2. Do 1. but import the shared parts from the simple package.
  3. Use subpackages in case that would result in removing dependency for the core subpackage.

What is a good way to fulfill the different needs?

Upvotes: 0

Views: 667

Answers (1)

Clasherkasten
Clasherkasten

Reputation: 492

I think optional dependencies are a pretty good use case for this. You could define an optional dependecy named your_package[fast] that installs pandas. And in your code you could try something like:

try:
    import pandas as pd
    PANDAS_INSTALLED = True
except ImportError:
    PANDAS_INSTALLED = False

# some other code...

if PANDAS_INSTALLED:
   def your_function(...):  # pandas installed
       ...
else:
   def your_function(...):  # pandas not installed 
       ...

Upvotes: 2

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